Statistics

The practice of advanced statistics normally requires the use of sophisticated software, not due to theoretical complexity but instead to sheer volume and repetition of required calculations. Without computers, advanced statistical number crunching would be too time consuming, especially with large data sets.

A course in advanced statistics will most likely follow the experience and particular interests of the professor in charge of the class. However, it is safe to say that whatever material is covered will most likely involve a sophisticated treatment of many of the following topics:

Descriptive statistical techniques

Probability theory

Random variables and probability distributions

Bivariate probability distributions

Discrete parametric probability distributions

Continuous parametric probability distributions

Sampling and the sampling distribution of a statistic

The chi-square, student's t, and Snedecor's F distributions

Point estimation and properties of point estimators

Interval estimation and confidence interval estimates

Tests of parametric statistical hypotheses

Nonparametric statistical techniques

Testing goodness of fit

Testing goodness of fit : contingency tables

Bivariate linear regression and correlation

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